Concept similarity analysis in Ontology’s automatic eztraction
Ontology’s automatic extraction is a core problem of Information Integration in Electronic Government Affair. In the process of ontology’s automatic extraction, FCA method is used in analyzing relationships between concepts automatically. But this method’s ability is insufficient in the analysis of the synonym relationship. This paper optimizes the FCA method and brings forward a new algorithm -SFCA. SFCA sets the weight for the attribute based on the importance of it. It computes the similarity degree using the weights and judges whether the concepts are synonymous. Through the analysis of the experiment’s result, the algorithm is validated to be effective. And its correctness proof is proved.
Information Integration Ontology Automatic eztraction FCA SFCA
Li Peng
School of Information Linyi Normal University Linyi China
国际会议
北京
英文
2201-2207
2009-08-08（万方平台首次上网日期，不代表论文的发表时间）